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Metaheuristics are widely used to solve important practical combinatorial optimization problems. Many new multicast applications emerging from the Internet-such as TV over the Internet, radio over the Internet, and multipoint video streaming-require reduced bandwidth consumption, end-to-end delay, and packet loss ratio. It is necessary to design and to provide for these kinds of applications as well as for those resources necessary for functionality. Multi-Objective Optimization in Computer Networks Using Metaheuristics provides a solution to the multi-objective problem in routing computer networks. It analyzes layer 3 (IP), layer 2 (MPLS), and layer 1 (GMPLS and wireless functions). In particular, it assesses basic optimization concepts, as well as several techniques and algorithms for the search of minimals; examines the basic multi-objective optimization concepts and the way to solve them through traditional techniques and through several metaheuristics; and demonstrates how to analytically model the computer networks presented within the text. The book then focuses on the multi-objective models in computer networks, optical networks, and wireless networks and the applied way they can be solved. This resource also contains annexes that present the source code to solve the mathematical model problems present in the book through solvers and source codes programmed in C language, which solve some of the multi-objective optimization problems presented in the book.

Metaheuristics are widely used to solve important practical combinatorial optimization problems. Many new multicast applications emerging from the Internet-such as TV over the Internet, radio over the Internet, and multipoint video streaming-require reduced bandwidth consumption, end-to-end delay, and packet loss ratio. It is necessary to design and to provide for these kinds of applications as well as for those resources necessary for functionality. Multi-Objective Optimization in Computer Networks Using Metaheuristics provides a solution to the multi-objective problem in routing computer networks. It analyzes layer 3 (IP), layer 2 (MPLS), and layer 1 (GMPLS and wireless functions). In particular, it assesses basic optimization concepts, as well as several techniques and algorithms for the search of minimals; examines the basic multi-objective optimization concepts and the way to solve them through traditional techniques and through several metaheuristics; and demonstrates how to analytically model the computer networks presented within the text. The book then focuses on the multi-objective models in computer networks, optical networks, and wireless networks and the applied way they can be solved. This resource also contains annexes that present the source code to solve the mathematical model problems present in the book through solvers and source codes programmed in C language, which solve some of the multi-objective optimization problems presented in the book.

Video coding is complex. YouTube and Netflix use it to deliver great video even at extremely low data rates. Have you ever wondered how they optimize video for low bandwidths? Do technical terms like 'rate distortion optimization', 'predictive coding' or 'adaptive quantization' overwhelm you? Decode To Encode is the only book that answers the hows and whys of elements in AVC (H.264), HEVC (H.265) and VP9. It provides video engineers and students all the compression fundamentals they need to solve problems, conduct research and serve their customers better. Coming from an experienced video codec engineer and product enthusiast, the book is written in a clear language with numerous examples.You will learn about:- digital video fundamentals and the evolution of codecs;- spatial and temporal aspects leveraged to achieve compression in block-based video architecture;- intra and inter coding, GOPs, block partitioning, prediction, transforms, quantization, CABAC, in-loop filtering, rate-distortion optimization and rate control;- bitrate modes, performance metrics and comparisons;- emerging topics like per-title encoding, AV1, 360 Video and VR, and encoding with ML.Why be left behind in today’s evolving video landscape? Get the tools you need to understand technical specifications and design video algorithms. Learn the concepts in this book and become a compression expert today. Exude confidence as you walk into your next meeting or start a conversation about video compression.

Video coding is complex. YouTube and Netflix use it to deliver great video even at extremely low data rates. Have you ever wondered how they optimize video for low bandwidths? Do technical terms like 'rate distortion optimization', 'predictive coding' or 'adaptive quantization' overwhelm you? Decode To Encode is the only book that answers the hows and whys of elements in AVC (H.264), HEVC (H.265) and VP9. It provides video engineers and students all the compression fundamentals they need to solve problems, conduct research and serve their customers better. Coming from an experienced video codec engineer and product enthusiast, the book is written in a clear language with numerous examples.You will learn about:- digital video fundamentals and the evolution of codecs;- spatial and temporal aspects leveraged to achieve compression in block-based video architecture;- intra and inter coding, GOPs, block partitioning, prediction, transforms, quantization, CABAC, in-loop filtering, rate-distortion optimization and rate control;- bitrate modes, performance metrics and comparisons;- emerging topics like per-title encoding, AV1, 360 Video and VR, and encoding with ML.Why be left behind in today’s evolving video landscape? Get the tools you need to understand technical specifications and design video algorithms. Learn the concepts in this book and become a compression expert today. Exude confidence as you walk into your next meeting or start a conversation about video compression.